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Whirrwork

Search robot jobs

search_use_cases
Read-onlyIdempotent

Find the robot job (use case) that matches what the buyer wants, in plain words and in any of 12 languages. Returns matching use cases (id, name, price summary, provider count) plus matching providers and guides. Start here, then call get_use_case with the best id. Examples: "drone light show for a wedding", "robotic floor scrubbing for a warehouse", "limpieza de ventanas con drones", "无人机灯光秀".

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYesWhat the buyer needs done, in their words
countryNoBuyer country: ISO 3166-1 alpha-2 ("AE") or English name ("United Arab Emirates").
languageNoLanguage for use-case text (machine-translated; English is authoritative). Default en.

Output Schema

NameRequiredDescriptionDefault
nextYes
queryYes
guidesNo
countryNo
languageNo
providersYes
use_casesYes
match_qualityNo
detected_languageNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly=true, idempotent=true, destructive=false, so the safety profile is covered. The description adds real value beyond them: multilingual query/text support, that it returns not just use cases but also matching providers and guides, and the id-to-detail chaining pattern. It doesn't discuss ambiguity in matching or empty-result behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose and next step in the first two clauses; no wasted preamble. The four inline examples plus the two already in the schema's query examples are mildly redundant, but they usefully demonstrate cross-lingual input.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema available, the description doesn't need to enumerate return fields, yet it summarizes them helpfully and covers the follow-up call. The only gap is any hint about the country filter or result-count limit for a 4-parameter search tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

At 75% schema coverage the schema already documents query, country, and language, and the description largely restates the natural-language/multilingual angle rather than adding syntax detail. The country filter and limit cap are never mentioned in the description, and "12 languages" conflicts with the 13-value language enum, a small but real inconsistency.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Find the robot job (use case)") plus scope ("in plain words and in any of 12 languages"). It is clearly distinguishable from siblings like find_providers, list_categories, and search_stats, and it explicitly names get_use_case as the follow-up.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Start here, then call get_use_case with the best id" gives an explicit entry point and next step in a multi-tool workflow. It stops short of saying when to prefer find_providers or compare_providers instead, so the routing is clear but not exhaustive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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